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Ruifang Li

Ruifang Li

Ruifang works mainly on data assimilation and in transferring HRRRv4/RAPv5 into FV3. We install capabilities required for DA in FV3 including latent heat forcing, cloud analysis and execute real-time and retrospective DA-cycling runs of regional FV3 at 12-km and 3-km, I also work on AOD and PM2.5 data assimilation for WildFire project. 

Research Interests

Education

  • M.S. in Computer Science, University of Oklahoma, Norman OK  — 2004
  • B.S. in Computer Science, Nanjing Institute of Meteorology, China  — 1994

Experience

Excellent scientific programming skill using Fortran and UNIX shell scripts to develop and apply functions for improving numerical weather simulation systems. Many years of experience in building and conducting end-to-end numerical experiments and analyzing the results. Profound knowledge on BUFR, GRIB1, and GRIB2 data structure and data process with NCEP and ECMWF libraries

Publications

Cucurull, L., R. Li, and T.R. Peevey, 2017: Assessment of Radio Occultation Observations from the COSMIC-2 Mission with a Simplified Observing System Simulation Experiment Configuration. Mon. Wea. Rev., 145, 3581–3597, https://doi.org/10.1175/MWR-D-16-0475.1

Cucurull, L., R. Atlas, R. Li, M.J. Mueller, and R.N. Hoffman, 2018: An Observing System Simulation Experiment with a Constellation of Radio Occultation Satellites. Mon. Wea. Rev., In review.

Boukabara, S., K. Ide, N. Shahroudi, Y. Zhou, T. Zhu, R. Li, L. Cucurull, R. Atlas, S.P. Casey, and R.N. Hoffman, 2018: Community Global Observing System Simulation Experiment (OSSE) Package (CGOP): Perfect Observations Simulation Validation. J. Atmos. Oceanic Technol., 35, 207–226, https://doi.org/10.1175/JTECH-D-17-0077.1

Boukabara, S., I. Moradi, R. Atlas, S.P. Casey, L. Cucurull, R.N. Hoffman, K. Ide, V. Krishna

Kumar, R. Li, Z. Li, M. Masutani, N. Shahroudi, J. Woollen, and Y. Zhou, 2016:Community Global Observing System Simulation Experiment (OSSE) Package (CGOP): Description and Usage. J. Atmos. Oceanic Technol., 33, 1759–1777,https://doi.org/10.1175/JTECH-D-16-0012.1

Our Mission

Lead research and directed development through the transition of environmental data, models, products, tools, and services to support commerce, protect life and property, and promote a scientifically literate public.

Research Areas

Organizational Excellence, Earth System Prediction, Advanced Technologies, and Decision Support are the foundation to achieving the GSL Grand Challenge: Deliver actionable global storm-scale prediction and environmental information through advanced technologies to serve society.

Global Systems Laboratory